Solution Architect – Data and Artificial Intelligence

Solution Architect – Data and Artificial Intelligence | Snowflake, Semantic Data Modelling and G&A Domains

We are seeking an experienced Solution Architect – Data and Artificial Intelligence to design and deliver scalable data products and artificial intelligence-enabled solutions for General and Administrative functions.

The ideal candidate will have strong expertise in Snowflake, semantic data modelling, cloud data platforms, and artificial intelligence, along with practical functional knowledge in one or more General and Administrative domains, such as Finance, Procurement, Human Resources, Corporate, Legal, Compliance, Communications, or Business Development.

This role combines technical architecture with business process understanding. The candidate will work closely with functional stakeholders to translate business requirements into governed, reusable data products and solutions. The architect will define end-to-end architectures, establish enterprise data standards, guide engineering teams, and develop practical delivery roadmaps aligned with business objectives.

Key Responsibilities

• Partner with General and Administrative stakeholders to understand business processes, challenges, key performance indicators, and data requirements.
  

• Define end-to-end data and artificial intelligence solution architectures aligned with enterprise standards.
  

• Design scalable data products on Snowflake, including data ingestion, transformation, storage, semantic modelling, and consumption.
  

• Develop canonical, dimensional, and semantic data models with consistent business definitions and reusable metrics.
  

• Establish shared key performance indicator definitions across Finance, Procurement, Human Resources, and other corporate functions.
  

• Identify appropriate artificial intelligence, machine learning, and generative artificial intelligence use cases.
  

• Design integrations across enterprise resource planning, procurement, human resources information systems, customer relationship management, legal, compliance, and other enterprise platforms.
  

• Provide architecture guidance across Snowflake, SQL, Python and cloud services.
  

Requirements

Significant experience as a Data Architect, Solution Architect, or Enterprise Architect delivering modern data platforms and data products.

Strong hands-on knowledge of Snowflake, including data architecture, performance, security, workload management, and cost optimization.

Strong experience in semantic data modelling, dimensional modelling, common business definitions, and enterprise key performance indicator design.

Demonstrable functional knowledge in at least two General and Administrative domains, preferably Finance, Procurement, or Human Resources.

Understanding of business processes such as record-to-report, procure-to-pay, budgeting and forecasting, workforce analytics, vendor management, or compliance reporting.

Experience integrating data from enterprise platforms such as enterprise resource planning, enterprise performance management, procurement, human resources information systems, or customer relationship management systems.

Strong knowledge of SQL and working knowledge of Python and modern transformation tools.

Experience designing governed data products for reporting, analytics, artificial intelligence, and self-service consumption.

Architecture experience on Amazon Web Services or Microsoft Azure.

Experience with business intelligence and semantic-layer technologies such as Power BI, Looker, Tableau.

Benefits

• Opportunities for professional growth and career development in data architecture and artificial intelligence.
  

• Exposure to Snowflake, semantic data modelling, cloud data platforms, and enterprise data products.
  

• Opportunity to design scalable and reusable data and artificial intelligence solutions.
  

• Collaboration with business stakeholders across Finance, Procurement, Human Resources, Legal, and Compliance.
  

• Experience working on enterprise data governance, data quality, security, and regulatory compliance.
  

• Opportunities to develop trusted enterprise metrics and semantic data models.
  

• Collaboration with cross-functional business, product, architecture, and engineering teams.
  

• Opportunity to contribute to artificial intelligence-enabled solutions and modern data transformation initiatives.